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Jens Sjolund

4 months ago

PhD in Computerized Image Processing and Physics-Informed Machine Learning for Green Hydrogen Production Uppsala University in Sweden

Degree Level

PhD

Field of study

Computer Science

Funding

PhD employment at 100% full time as a temporary position under Uppsala University rules. The post may include up to 20% departmental duties such as teaching and administration. Salary is fixed salary; no stipend amount is stated.

Deadline

Expired

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Country

Sweden

University

Uppsala University

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Keywords

Computer Science
Machine Learning
Electrical Engineering
Materials Science
Deep Learning
Mathematics
Image Processing
Computer Vision
Digital Twin Technology
Hydrogen Technology
Ct Imaging
Physics

About this position

Uppsala University is recruiting a PhD student in computerized image processing and physics-informed machine learning for green hydrogen production. The project sits at the intersection of computer science, machine learning, computer vision, physics-informed modeling, materials science, and mathematics, with a strong application focus on accelerating Sweden’s transition to green hydrogen.

The research will study proton exchange membrane water electrolyzers (PEMWE) and thermally sprayed titanium layers used for corrosion protection. The PhD student will develop automated pipelines for X-ray computed tomography (XCT) image segmentation and analysis, extract physically meaningful microstructural descriptors, build probabilistic surrogate models and a digital twin linking microstructure to electrochemical performance, and use Bayesian experimental design and process optimization to guide manufacturing parameters. The work is supervised by Ida-Maria Sintorn and Jens Sjölund at the Department of Information Technology, Uppsala University, in collaboration with Alleima and Sandvik.

Eligible backgrounds include engineering physics, electrical engineering, image processing, computer vision, AI, machine learning, data science, computer science, and applied mathematics, or equivalent qualifications. Strong programming skills, preferably in Python, excellent study results, and good English communication skills are expected. Experience in image analysis, deep learning, optimization, numerical linear algebra, visualization, and software engineering is considered an advantage.

The position is a temporary full-time PhD employment at Uppsala University. The employment may include up to 20% departmental duties such as teaching and administration. The starting date is 1 September 2026 or as agreed. The application deadline is 7 May 2026.

To apply, prepare a cover letter in English, a CV, degree documents and transcripts, thesis or scientific writing samples, publications, and reference details. Submit the application through Uppsala University’s recruitment system.

Funding details

PhD employment at 100% full time as a temporary position under Uppsala University rules. The post may include up to 20% departmental duties such as teaching and administration. Salary is fixed salary; no stipend amount is stated.

What's required

Applicants must hold a Master’s degree in engineering physics, electrical engineering, image processing, computer vision, AI, machine learning, data science, computer science, applied mathematics, or a similar field, or have completed at least 240 higher-education credits including at least 60 credits at Master’s level with an independent project worth at least 15 credits, or have equivalent knowledge. Strong interest in new methods for image processing, computational mathematics, and machine learning is required, along with excellent study results, high proficiency in programming preferably in Python, good oral and written English, and personal qualities such as creativity, thoroughness, and a structured approach to problem-solving. Coursework or experience in image analysis, machine learning, linear algebra, calculus, numerical linear algebra, optimization, statistical machine learning, computer vision, 3D image processing, visualization, material science, deep learning, and software engineering are valued.

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